groupby() seems slow

[7stud]

I'm applying groupby() in a very simplistic way to split up some data,
but when I timeit against another method, it takes twice as long.  The
following groupby() code groups the data between the "</tr>" strings:

data = [
"1.5","</tr>","2.5","3.5","4.5","</tr>","</tr>","5.5","6.5","</tr>",
"1.5","</tr>","2.5","3.5","4.5","</tr>","</tr>","5.5","6.5","</tr>",
"1.5","</tr>","2.5","3.5","4.5","</tr>","</tr>","5.5","6.5","</tr>",
]

import itertools

def key(s):
    if s[0] == "<":
        return 'a'
    else:
        return 'b'

def test3():

    master_list = []
    for group_key, group in itertools.groupby(data, key):
        if group_key == "b":
            master_list.append(list(group) )


def test1():
    master_list = []
    row = []

    for elmt in data:
        if elmt[0] != "<":
            row.append(elmt)
        else:
            if row:
                master_list.append(" ".join(row) )
                row = []


import timeit

t = timeit.Timer("test3()", "from __main__ import test3, key, data")
print t.timeit()
t = timeit.Timer("test1()", "from __main__ import test1, data")
print t.timeit()

--output:---
42.791079998
19.0128788948

I thought groupby() would be faster.  Am I doing something wrong?